Kaiserslautern, University, Diss., 2002.

Berlin, Freie University, Diss., 2001. / Dateiformat: zip, Dateien im PDF-Format.

München, Techn. University, Diss., 2002.

This paper presents prediction intervals for the multiple linear regression model after forward selection. The prediction interval is for a future value of the response variable Yf given a p×1 vector of predictors xf

L'objectif de ce travail de thèse était d'évaluer l'intérêt de mettre en place des évaluations génomiques dans les programmes de sélection porcins. Des simulations stochastiques ont été réalisées dans le cas d'un programme de sélection d'une lignée mâle de grande taille contenant 1 050 femelles reproductrices et 50 verrats, sélectionnée pendant 10 ans pour améliorer un objectif de sélection combinant 2 caractères, respectivement mesurés sur 13 770 candidats par an (Car1) et sur 270 collatéraux par an (Car2) issus de 10% des portées. Dans la situation de référence, les valeurs génétiques étaient estimées selon la méthodologie du BLUP-Modèle Animal (BLUPMA). Dans une première étude, nous avons comparé le scénario BLUPMA à un scénario génomique dans lequel tous les candidats étaient génotypés. Les évaluations génomiques s'appuyaient sur deux populations de référence (PR) initialement constituées de 13 770 candidats pour Car1 et de 1 000 collatéraux pour Car2, et dont les tailles respectives augmentaient annuellement, en considérant les mêmes capacités de phénotypage que dans le scénario BLUPMA. Les résultats montrent que des évaluations génomiques améliorent nettement la précision d'estimation des valeurs génétiques des candidats pour les deux caractères et le progrès génétique réalisé annuellement sur l'objectif global de sélection (+27% à +33% selon les héritabilités considérées), tout en réduisant significativement l'augmentation de la consanguinité dans la population. Un second scénario génomique a été simulé, dans lequel les candidats n'étaient plus phénotypés et les évaluations génomiques s'appuyaient sur une PR uniquement constituée de collatéraux phénotypés pour Car1 et Car2. Dans ce cas, la précision des valeurs génomiques estimées et la réponse à la sélection pour Car1 sont nettement plus faibles que dans le scénario BLUPMA, montrant que la sélection génomique ne permet pas de mettre fin au phénotypage des animaux. La mise en place d'évaluations génomiques nécessitant de génotyper un grand nombre d'individus, elle entraîne un surcoût important par rapport au scénario BLUPMA. Dans une seconde étude, nous avons montré que ce surcoût peut être largement réduit en présélectionnant les candidats à génotyper sur la base de leur valeur génomique estimée sur ascendance. Il est ainsi possible de réduire de manière significative le nombre de candidats à génotyper tout en préservant une grande partie de l'avantage de la sélection génomique par rapport à la sélection conventionnelle BLUPMA. Ainsi, une diminution de 40% du nombre de candidats génotypés ne réduit que de 3 à 4% le progrès génétique annuel sur l'objectif global. Nous avons également montré qu'au-delà d'un certain seuil d'investissement, une dépense supplémentaire pour améliorer l'efficacité du programme de sélection est plus efficacement investie dans la mise en place d'évaluations génomiques que dans l'augmentation de la capacité de phénotypage des collatéraux dans le dispositif conventionnel. Ce seuil d'intérêt de mise en place d'un programme génomique est d'autant plus bas que le coût du génotypage est faible et que le coût de phénotypage des collatéraux est élevé. L'ensemble de nos résultats suggère qu'il serait intéressant de mettre en place des évaluations génomiques dans un programme de sélection d'une lignée porcine mâle de grande taille, notamment dans la population Piétrain collective française, dont la structure est proche de celle de la population simulée dans nos études. / The aim of this work was to evaluate the interest of implementing genomic evaluations in pig breeding schemes. Stochastic simulation was used. The simulated population was a pig sire line containing 1,050 breeding females and 50 boars. The line was selected for 10 years for a breeding goal including two uncorrelated traits, recorded on, respectively, 13,770 candidates per year (trait1) and 270 relatives per year born in 10% of the litters (trait2). In the reference breeding scheme (BLUPAM), the selection was based on pedigree-based BLUP estimated breeding values (EBVs). In a first study, we compared the BLUPAM scenario to an alternative genomic breeding scheme with the same phenotyping capacities, where all candidates for selection were genotyped. The genomic breeding values for trait1 and trait2 were estimated using two training populations (TP). The first one (TP1) was made up of selection candidates (phenotyped for trait1) and the second one (TP2) of relatives phenotyped for trait2. The size of TP1 and TP2 increased, respectively, from 13,770 to 55,080 and from 1,000 to 3,430 over time. Our results show that genomic evaluations significantly improve the accuracy of the EBVs of the candidates for both traits and therefore the annual genetic trends for the global breeding goal (+27% to +33% depending on trait heritability), while significantly reducing the inbreeding rate. A second genomic scenario was simulated, in which the candidates were no longer phenotyped for trait1, and the genomic breeding values were estimated with one single TP made up of relatives phenotyped for both traits. In that case, the accuracy of EBVs and the annual genetic trends for trait1 are significantly lower than in the reference (BLUPAM) scenario. This shows that a large TP is required to outperform the current schemes for traits recorded on the candidates. The implementation of genomic evaluations requires the genotyping of a large number of animals, and therefore generates additional costs compared to BLUPAM breeding schemes. In a second study, we showed that genotyping a subset of candidates that have been pre-selected according to their parental EBV allows to significantly reduce the extra costs of a genomic breeding scheme while preserving most of its superiority in terms of genetic trends and inbreeding over the BLUPAM breeding scheme. For instance, reducing the number of genotyped candidates by 40% only reduced by 3 to 4% the global annual genetic trend. We also showed that even a very marked increase in the number of relatives phenotyped for trait2 in a BLUPAM scenario does not allow to be as efficient as a genomic scenario when the number of genotyped candidates is large. Finally, we showed that the economic interest of genetic selection can be characterized by an additional cost threshold; below this threshold, it is preferable to maintain pedigree-based BLUP evaluations and increase the number of relatives, while implementing genomic evaluation is more efficient above this threshold. The value of this threshold depends on the cost of phenotyping additional relatives and on genotyping costs.Our results suggest that implementing genomic evaluations in a large size pig sire line can be a valuable strategy. This strategy could for instance easily be applied to the French Piétrain population, which resembles the nucleus population simulated in this study.

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While the existence of costs of mate choice is well accepted, the effects that these costs have on mating systems and the evolution of mate choice are controversial. The aim of this thesis is to explore a range of different types of costs, including costs of being choosy (using guppies, Poecilia reticulata) and costs of mating with attractive males (using house crickets, Acheta domesticus), and investigate how these costs influence female mating behaviour, sexual selection on males and the evolution of mate choice. I use a range of experimental techniques to investigate these questions including: comparisons of feral populations of guppies (Chapter Two), laboratory experiments that manipulate the social (sex ratio, density; Chapters Three and Four) and physical (water current; Chapter Five) environment in which guppies live, genetic paternity analysis and multivariate selection analysis (Chapter Four). I also conduct longitudinal studies of house crickets that estimate the net fitness consequences (Chapter Six) and indirect effects (Chapter Six and Seven) of mating with attractive males. My results demonstrate that the physical and social environment of individuals are important in determining the costliness of both sexual display and mate choice, and thus influence the mating behaviour of males and females. These differences in mating behaviour are often thought to lead to differences in sexual selection on males. My study of the effects of operational sex ratio and density on multivariate sexual selection, however, indicates that differences in behaviour may not necessarily translate into differences in selection. In contrast to predictions of recent theory, my results also indicate that although there are many costs to being choosy and to mating with attractive males, these may be outweighed by indirect benefits. Hence, despite direct costs of choice, mate choice may evolve via indirect benefits to females. Indirect benefits that are often neglected in sexual selection studies, that I show to be important in determining the net fitness of mating with attractive males, include the attractiveness of sons and the mate choice decisions of daughters. These results highlight the importance of examining the consequences of mate choice over multiple generations.

Natural selection acts on multiple traits simultaneously. How mechanisms underlying such traits enable or constrain their response to simultaneous selection is poorly understood. We show how antagonism and synergism among three traits at the developmental level enable or constrain evolutionary change in response to simultaneous selection on two focal traits at the phenotypic level. After 10 generations of 25% simultaneous directional selection on all four combinations of body size and development time in Manduca sexta (Sphingidae), the changes in the three developmental traits predict 93% of the response of development time and 100% of the response of body size. When the two focal traits were under synergistic selection, the response to simultaneous selection was enabled by juvenile hormone and ecdysteroids and constrained by growth rate. When the two focal traits were under antagonistic selection, the response to selection was due primarily to change in growth rate and constrained by the two hormonal traits. The approach used here reduces the complexity of the developmental and endocrine mechanisms to three proxy traits. This generates explicit predictions for the evolutionary response to selection that are based on biologically informed mechanisms. This approach has broad applicability to a diverse range of taxa, including algae, plants, amphibians, mammals, and insects.

The multivariate distribution of genetic variance is key to understanding two fundamental and interrelated processes in evolution; the ability of populations to respond to selection, and the balance of forces that maintain the genetic variance that such a response is based upon. In this thesis, I develop an analytical framework for characterizing the multivariate distribution of genetic variance and how it evolves. I then apply this framework to explore the evolution of genetic variance in multiple sexually-selected traits under artificial selection using the Drosophila serrata experimental system. An analytical framework for characterizing the multivariate distribution of genetic variance and how it evolves: First, I present a method from the statistical literature to establish the statistical dimensionality of genetic variance in a suite of traits. I evaluate the ability of this and two other methods to predict the correct number and orientation of dimensions of genetic variance by conducting a simulation study for a suite of eight traits. Second, I present a method from the materials science literature that uses multi-linear algebra to characterize the variation among matrices. I show how variation in the multivariate distribution of genetic variance among populations can be analyzed by constructing a fourth-order genetic variance-covariance tensor, and how the spectral decomposition of this tensor reveals independent aspects of change in genetic variance. I use the tensor to explore the variation in the genetic variance of eight traits among nine populations of D. serrata, and show how this variation can be associated with variation in selection pressures to determine whether selection may have affected genetic variance within populations. The evolution of genetic variance in sexually-selected traits under artificial selection: Female D. serrata display a strong preference for a particular combination of male cuticular hydrocarbons (CHCs). Individually, these pheromones display substantial genetic variance, but the genetic variance is not distributed equally among all phenotypic dimensions. In the specific CHC combination preferred by females, genetic variance is low. This is compatible with the expectation that selection will deplete genetic variance, but is contrary to the typical observation of high levels of genetic variance in individual sexually-selected traits. By artificially selecting on the trait combination preferred by females, I show that male mating success can successfully respond to selection, but the evolution of the combination of CHCs preferred by females is constrained. I then show that a key prediction of mutation-selection balance (MSB) models that has rarely been observed holds for these traits. Under MSB, genetic variance is expected to be maintained by rare alleles with large effects. Therefore, when a trait that is usually under stabilizing selection is subjected to directional artificial selection, the genetic variance is predicted to increase. I show that genetic variance increases in the CHC combination preferred by females under artificial selection, but not when another combination of the same traits with greater genetic variance is artificially selected. Complex segregation analysis indicated that the observed increase in genetic variance was a consequence of at least one allele of major effect increasing in frequency. This experiment demonstrates the importance of the past history of selection on the nature of genetic variance. General conclusion: Mutation-selection balance (MSB) is appealing as an explanation for the maintenance of genetic variance because it is simple and intuitive: the total mutation rate must be sufficiently high to replenish the variation eliminated by selection. However, MSB models seem unable to adequately explain the coexistence of the observed levels of genetic variance and strength of selection on individual traits. I contend that the failure of MSB models to explain these data is not a failure of MSB theory itself; rather it is the data that has been used to evaluate MSB models that may not be appropriate. It is now clear that there are fewer genetically independent traits than measured phenotypes, and that selection gradients measured for individual traits do not adequately reflect the nature of selection on combinations of traits. In other words, it is not possible to understand the relationship between genetic variance and selection by simply associating median levels of genetic variance and selection collated across studies as levels of genetic variance are likely to be much lower in trait combinations associated with stronger selection. Together, these observations suggest that we should be looking at the distribution of genetic variance in suites of traits and pattern of correlated selection on those same traits if we are to understand MSB.

This research tests the descriptive validity of Ouchi's model of organizational control when it is applied to auditing firms. An analysis of Ouchi's model and other writings indicates that the selection-socialization type of control (or clan control or control by a strong organizational culture) would be expected to be used in auditing firms and that it would he evidenced by similarities in values perceived to be held by clan members. Empirical evidence is gathered from graduating students who are accounting majors and from professional staff in auditing firms using SYMLOG to measure perceived values. This evidence provided some support for the descriptive validity of Ouchi's model, but the evidence is mixed. The sets of perceived values found in staff of auditing firms do not appear to come from a single set, but the perceived values of each firm are different. Offers do appear to be made to individuals who have different sets of perceived values when compared to people who did not receive offers. No evidence was found to indicate that length of association within firm results in more similar sets of perceived values being held by firm members.